Paclitaxel plus Bevacizumab versus Paclitaxel Alone for Metastatic Breast Cancer
Bibliographic record
Abstract
BACKGROUND: In an open-label, randomized, phase 3 trial, we compared the efficacy and safety of paclitaxel with that of paclitaxel plus bevacizumab, a monoclonal antibody against vascular endothelial growth factor, as initial treatment for metastatic breast cancer. METHODS: We randomly assigned patients to receive 90 mg of paclitaxel per square meter of body-surface area on days 1, 8, and 15 every 4 weeks, either alone or with 10 mg of bevacizumab per kilogram of body weight on days 1 and 15. The primary end point was progression-free survival; overall survival was a secondary end point. RESULTS: From December 2001 through May 2004, a total of 722 patients were enrolled. Paclitaxel plus bevacizumab significantly prolonged progression-free survival as compared with paclitaxel alone (median, 11.8 vs. 5.9 months; hazard ratio for progression, 0.60; P<0.001) and increased the objective response rate (36.9% vs. 21.2%, P<0.001). The overall survival rate, however, was similar in the two groups (median, 26.7 vs. 25.2 months; hazard ratio, 0.88; P=0.16). Grade 3 or 4 hypertension (14.8% vs. 0.0%, P<0.001), proteinuria (3.6% vs. 0.0%, P<0.001), headache (2.2% vs. 0.0%, P=0.008), and cerebrovascular ischemia (1.9% vs. 0.0%, P=0.02) were more frequent in patients receiving paclitaxel plus bevacizumab. Infection was more common in patients receiving paclitaxel plus bevacizumab (9.3% vs. 2.9%, P<0.001), but febrile neutropenia was uncommon (<1% overall). CONCLUSIONS: Initial therapy of metastatic breast cancer with paclitaxel plus bevacizumab prolongs progression-free survival, but not overall survival, as compared with paclitaxel alone. (ClinicalTrials.gov number, NCT00028990 [ClinicalTrials.gov].).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".